colibri is live on @TheDAOFund. We're building proof-based verification infrastructure that closes the RPC trust gap — the attack surface that made KelpDAO possible. Zero bugs in the contracts. The data layer was compromised. A couple of production integrations already shipping: @FreedomBrowser and the @ethFoundation Kohaku Wallet SDK. Co-funders welcome. The initiative is open. initiatives.thedao.fund #DeFi #Web3Security #BridgeSecurity

colibri-stateless v3 is out — full Glamsterdam/GLOAS support, shipped ahead of the fork. If you're verifying against Sepolia: move to v3 before Oct 6, 13:53 UTC (epoch 353024). The old proof paths don't carry over. 👇

PragmaticAdaptivePrivacy doesn't require new blockchains, new consensus mechanisms, or new smart contracts. It's deployable today, in existing infrastructure, across wallets, DeFi protocols, AI agents, and IoT devices. #Web3Privacy #DeFi #Ethereum

What this looks like in practice: Wallet — balance checks and simulations don't expose trade intent before submission. Front-running vector closed. DeFi Protocol — routing queries and liquidity checks protected. Privacy becomes a property of the protocol, not a responsibility delegated to users. AI Agent — Privacy Profiles adjust dynamically as the agent moves from observation to strategic decision-making. IoT Device — lightweight profiles provide meaningful protection within bandwidth and compute constraints.

Not every information leak is a practical security risk. Whether leaked information matters depends on whether it can be exploited — and when. #Web3Privacy #DeFi

This is the key principle behind C1 — pragmatic Content Privacy. A wallet preparing a swap doesn't issue a narrow sequence revealing one exact route and amount. It requests a broader set of state data, evaluates locally, and executes. An observer may see that the user is interested in a market. They cannot reliably infer the exact trade in time to exploit it. C1 doesn't try to hide that an interaction exists. It prevents that interaction from being turned into actionable intelligence within the window.

Privacy in Web3 is not binary. Different operations, environments, and threat models require different levels of protection. #PragmaticAdaptivePrivacy (#PAP) models this with two independent dimensions. 🧵 #Web3Privacy #TrustlessVerification

These dimensions are orthogonal. Strong Transport Privacy doesn't prevent intent leakage if the request remains highly specific. Strong Content Privacy doesn't prevent profiling if all requests can still be correlated to the same identity. Both dimensions must be addressed simultaneously. A Privacy Profile combines one level from each: T1/C1 for routine operations. T2/C2 for high-stakes decisions. The profile describes requirements — not the mechanisms used to achieve them.

Privacy and verifiability are not in tension. They're both requirements. A system that achieves one by sacrificing the other isn't a privacy solution. It's a trade-off dressed up as one. #Web3Privacy #TrustlessVerification

Three requirements define the design space for a viable Web3 privacy model: Trustless — no reliance on intermediaries; compatible with independent verification. Adaptive — a balance check and an institutional trade don't carry the same risk profile. Uniform protection is either excessive or insufficient. Resource-efficient — usable in browsers, mobile environments, IoT. High overhead makes a solution impractical regardless of its theoretical strength.